{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Automatic mixed precision training and evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial shows how to apply the automatic mixed precision (AMP) feature of PyTorch to training and validation programs.  \n",
    "It's modified from the Spleen 3D segmentation tutorial notebook, and compares the training speed and memory usage with/without AMP.\n",
    "\n",
    "The Spleen dataset can be downloaded from http://medicaldecathlon.com/."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Copyright 2020 MONAI Consortium\n",
    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#     http://www.apache.org/licenses/LICENSE-2.0\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License.\n",
    "\n",
    "import os\n",
    "import glob\n",
    "import time\n",
    "import numpy as np\n",
    "import torch\n",
    "from torch.utils.data import DataLoader\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from monai.config import get_torch_version_tuple\n",
    "from monai.data import Dataset, CacheDataset, list_data_collate\n",
    "from monai.transforms import \\\n",
    "    Compose, LoadNiftid, AddChanneld, ScaleIntensityRanged, CropForegroundd, \\\n",
    "    RandCropByPosNegLabeld, RandAffined, Spacingd, Orientationd, ToTensord\n",
    "from monai.inferers import sliding_window_inference\n",
    "from monai.networks.layers import Norm\n",
    "from monai.networks.nets import UNet\n",
    "from monai.losses import DiceLoss\n",
    "from monai.metrics import compute_meandice\n",
    "from monai.utils import set_determinism\n",
    "\n",
    "if get_torch_version_tuple() < (1, 6):\n",
    "    raise RuntimeError('AMP feature only exists in PyTorch version greater than v1.6.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set MSD Spleen dataset path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_root = '/workspace/data/medical/Task09_Spleen'\n",
    "train_images = sorted(glob.glob(os.path.join(data_root, 'imagesTr', '*.nii.gz')))\n",
    "train_labels = sorted(glob.glob(os.path.join(data_root, 'labelsTr', '*.nii.gz')))\n",
    "data_dicts = [{'image': image_name, 'label': label_name}\n",
    "              for image_name, label_name in zip(train_images, train_labels)]\n",
    "train_files, val_files = data_dicts[:-9], data_dicts[-9:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup transforms for training and validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def transformations():\n",
    "    train_transforms = Compose([\n",
    "        LoadNiftid(keys=['image', 'label']),\n",
    "        AddChanneld(keys=['image', 'label']),\n",
    "        Spacingd(keys=['image', 'label'], pixdim=(1.5, 1.5, 2.), mode=('bilinear', 'nearest')),\n",
    "        Orientationd(keys=['image', 'label'], axcodes='RAS'),\n",
    "        ScaleIntensityRanged(keys=['image'], a_min=-57, a_max=164, b_min=0.0, b_max=1.0, clip=True),\n",
    "        CropForegroundd(keys=['image', 'label'], source_key='image'),\n",
    "        # randomly crop out patch samples from big image based on pos / neg ratio\n",
    "        # the image centers of negative samples must be in valid image area\n",
    "        RandCropByPosNegLabeld(keys=['image', 'label'], label_key='label', spatial_size=(96, 96, 96), pos=1,\n",
    "                               neg=1, num_samples=4, image_key='image', image_threshold=0),\n",
    "        ToTensord(keys=['image', 'label'])\n",
    "    ])\n",
    "    val_transforms = Compose([\n",
    "        LoadNiftid(keys=['image', 'label']),\n",
    "        AddChanneld(keys=['image', 'label']),\n",
    "        Spacingd(keys=['image', 'label'], pixdim=(1.5, 1.5, 2.), mode=('bilinear', 'nearest')),\n",
    "        Orientationd(keys=['image', 'label'], axcodes='RAS'),\n",
    "        ScaleIntensityRanged(keys=['image'], a_min=-57, a_max=164, b_min=0.0, b_max=1.0, clip=True),\n",
    "        CropForegroundd(keys=['image', 'label'], source_key='image'),\n",
    "        ToTensord(keys=['image', 'label'])\n",
    "    ])\n",
    "    return train_transforms, val_transforms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define a typical PyTorch training process\n",
    "Usage of PyTorch AMP module refers to: https://pytorch.org/docs/stable/notes/amp_examples.html."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def train_process(amp=False):\n",
    "    train_trans, val_trans = transformations()\n",
    "    train_ds = CacheDataset(data=train_files, transform=train_trans, cache_rate=1.0, num_workers=4)\n",
    "    val_ds = CacheDataset(data=val_files, transform=val_trans, cache_rate=1.0, num_workers=4)\n",
    "\n",
    "    # use batch_size=2 to load images and use RandCropByPosNegLabeld\n",
    "    # to generate 2 x 4 images for network training\n",
    "    train_loader = DataLoader(train_ds, batch_size=2, shuffle=True, num_workers=4, collate_fn=list_data_collate)\n",
    "    val_loader = DataLoader(val_ds, batch_size=1, num_workers=4)\n",
    "    device = torch.device('cuda:0')\n",
    "    model = UNet(dimensions=3, in_channels=1, out_channels=2, channels=(16, 32, 64, 128, 256),\n",
    "                 strides=(2, 2, 2, 2), num_res_units=2, norm=Norm.BATCH).to(device)\n",
    "    loss_function = DiceLoss(to_onehot_y=True, softmax=True)\n",
    "    optimizer = torch.optim.Adam(model.parameters(), 1e-4)\n",
    "    scaler = torch.cuda.amp.GradScaler() if amp else None\n",
    "\n",
    "    epoch_num = 600\n",
    "    val_interval = 1  # do validation for every epoch\n",
    "    best_metric = -1\n",
    "    best_metric_epoch = -1\n",
    "    epoch_loss_values = list()\n",
    "    metric_values = list()\n",
    "    epoch_times = list()\n",
    "    total_start = time.time()\n",
    "    for epoch in range(epoch_num):\n",
    "        epoch_start = time.time()\n",
    "        print('-' * 10)\n",
    "        print(f\"epoch {epoch + 1}/{epoch_num}\")\n",
    "        model.train()\n",
    "        epoch_loss = 0\n",
    "        step = 0\n",
    "        for batch_data in train_loader:\n",
    "            step_start = time.time()\n",
    "            step += 1\n",
    "            inputs, labels = batch_data['image'].to(device), batch_data['label'].to(device)\n",
    "            optimizer.zero_grad()\n",
    "            if amp and scaler is not None:\n",
    "                with torch.cuda.amp.autocast():\n",
    "                    outputs = model(inputs)\n",
    "                    loss = loss_function(outputs, labels)\n",
    "                scaler.scale(loss).backward()\n",
    "                scaler.step(optimizer)\n",
    "                scaler.update()\n",
    "            else:\n",
    "                outputs = model(inputs)\n",
    "                loss = loss_function(outputs, labels)\n",
    "                loss.backward()\n",
    "                optimizer.step()\n",
    "            epoch_loss += loss.item()\n",
    "            print(f\"{step}/{len(train_ds) // train_loader.batch_size}, train_loss: {loss.item():.4f}\"\n",
    "                  f\" step time: {(time.time() - step_start):.4f}\")\n",
    "        epoch_loss /= step\n",
    "        epoch_loss_values.append(epoch_loss)\n",
    "        print(f\"epoch {epoch + 1} average loss: {epoch_loss:.4f}\")\n",
    "\n",
    "        if (epoch + 1) % val_interval == 0:\n",
    "            model.eval()\n",
    "            with torch.no_grad():\n",
    "                metric_sum = 0.\n",
    "                metric_count = 0\n",
    "                for val_data in val_loader:\n",
    "                    val_inputs, val_labels = val_data['image'].to(device), val_data['label'].to(device)\n",
    "                    roi_size = (160, 160, 160)\n",
    "                    sw_batch_size = 4\n",
    "                    if amp:\n",
    "                        with torch.cuda.amp.autocast():\n",
    "                            val_outputs = sliding_window_inference(val_inputs, roi_size, sw_batch_size, model)\n",
    "                    else:\n",
    "                        val_outputs = sliding_window_inference(val_inputs, roi_size, sw_batch_size, model)\n",
    "                    value = compute_meandice(y_pred=val_outputs, y=val_labels, include_background=False,\n",
    "                                             to_onehot_y=True, mutually_exclusive=True)\n",
    "                    metric_count += len(value)\n",
    "                    metric_sum += value.sum().item()\n",
    "                metric = metric_sum / metric_count\n",
    "                metric_values.append(metric)\n",
    "                if metric > best_metric:\n",
    "                    best_metric = metric\n",
    "                    best_metric_epoch = epoch + 1\n",
    "                    torch.save(model.state_dict(), 'best_metric_model.pth')\n",
    "                    print('saved new best metric model')\n",
    "                print(f\"current epoch: {epoch + 1} current mean dice: {metric:.4f}\"\n",
    "                      f\" best mean dice: {best_metric:.4f} at epoch: {best_metric_epoch}\")\n",
    "        print(f\"time consuming of epoch {epoch + 1} is: {(time.time() - epoch_start):.4f}\")\n",
    "        epoch_times.append(time.time() - epoch_start)\n",
    "    print(f\"train completed, best_metric: {best_metric:.4f} at epoch: {best_metric_epoch}\"\n",
    "          f\" total time: {(time.time() - total_start):.4f}\")\n",
    "    return epoch_num, epoch_loss_values, metric_values, epoch_times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Enable deterministic and train with AMP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "set_determinism(seed=0)\n",
    "amp_start = time.time()\n",
    "epoch_num, amp_epoch_loss_values, amp_metric_values, amp_epoch_times = train_process(amp=True)\n",
    "amp_total_time = time.time() - amp_start\n",
    "print(f\"total training time of {epoch_num} epochs with AMP: {amp_total_time:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Expected memory usage during training with AMP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image](./images/mem_amp_on.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Enable deterministic and train without AMP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "set_determinism(seed=0)\n",
    "start = time.time()\n",
    "epoch_num, epoch_loss_values, metric_values, epoch_times = train_process(amp=False)\n",
    "total_time = time.time() - start\n",
    "print(f\"total training time of {epoch_num} epochs without AMP: {total_time:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Expected memory usage during training without AMP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image](./images/mem_amp_off.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot training loss and validation metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('train', (12, 12))\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.title('Regular Epoch Average Loss')\n",
    "x = [i + 1 for i in range(len(epoch_loss_values))]\n",
    "y = epoch_loss_values\n",
    "plt.xlabel('epoch')\n",
    "plt.grid(alpha=0.4, linestyle=':')\n",
    "plt.plot(x, y, color='red')\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.title('Regular Val Mean Dice')\n",
    "x = [i + 1 for i in range(len(metric_values))]\n",
    "y = metric_values\n",
    "plt.xlabel('epoch')\n",
    "plt.grid(alpha=0.4, linestyle=':')\n",
    "plt.plot(x, y, color='red')\n",
    "\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.title('AMP Epoch Average Loss')\n",
    "x = [i + 1 for i in range(len(amp_epoch_loss_values))]\n",
    "y = amp_epoch_loss_values\n",
    "plt.xlabel('epoch')\n",
    "plt.grid(alpha=0.4, linestyle=':')\n",
    "plt.plot(x, y, color='green')\n",
    "\n",
    "plt.subplot(2, 2, 4)\n",
    "plt.title('AMP Val Mean Dice')\n",
    "x = [i + 1 for i in range(len(amp_metric_values))]\n",
    "y = amp_metric_values\n",
    "plt.xlabel('epoch')\n",
    "plt.grid(alpha=0.4, linestyle=':')\n",
    "plt.plot(x, y, color='green')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot total time and every epoch time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('train', (12, 6))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.title('Total Train Time(600 epochs)')\n",
    "plt.bar('regular', total_time, 1, label='Regular training', color='red')\n",
    "plt.bar('AMP', amp_total_time, 1, label='AMP training', color='green')\n",
    "plt.ylabel('secs')\n",
    "plt.grid(alpha=0.4, linestyle=':')\n",
    "plt.legend(loc='best')\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.title('Epoch Time')\n",
    "x = [i + 1 for i in range(len(epoch_times))]\n",
    "plt.xlabel('epoch')\n",
    "plt.ylabel('secs')\n",
    "plt.plot(x, epoch_times, label='Regular training', color='red')\n",
    "plt.plot(x, amp_epoch_times, label='AMP training', color='green')\n",
    "plt.grid(alpha=0.4, linestyle=':')\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
